Article Preview
Top1. Introduction
The tremendous growth of video websites, such as Yahoo Video, YouTube, and social networks, such as Google+, Facebook are also grown very rapidly over the internet. The video containing the following features: Initially, the video consists of several affluent contents than individual images, then the videos consist of huge raw data (Menaga and Begum, 2020), and finally, the video has a little prior structure. The above-mentioned features make video indexing and retrieval complicated. Thus, the existing video databases are very small and therefore, the indexing and the retrieval are performed on the basis of keywords that are manually annotated. In addition, the databases are huge, and hence, content-based indexing and retrieval are carried out using less human intervention based on the video analysis automatically. Some of the widespread applications (Preetha, 2018) utilized in the content-driven video retrieval and indexing are fast browsing of the video contents (Madhuri, 2016), digital museums, visual electronic are examined using the commerce remote instruction, news event analysis (Peng and Ngo, 2005), the video surveillance and the web service are managed intelligently. The main aim of the video standards is to certify the compatibility among the description of video files to enable accurate and fast video retrieval approaches. Some of the main standards utilized in the videos are Moving Picture Experts Group (MPEG) as well as TV-Anytime Standard (Pereira, et al., 2008;Babu and Ramakrishnan, 2007;Hu, et al., 2011).
The video summarization has been paid great attention for managing the videos on web and for extracting the information. The main aim of the video summarization is to generate a short summary video for providing the users a very useful visual and synthetic abstract of the video content. In addition, video summarization is the tool to produce the short memory of video, which means the sequence of stationary images known as moving images, keyframes or the video skims. Video summarization is the process for facilitating fast browsing among the huge video collections and provides content indexing very efficiently (Wagdarikar and Senapati, 2019). Video summarization refers to create a video summary that should be addressed the below-mentioned points. a) the video summary must contain events and the scenes, b) the continuous connection between the scenes should be maintained, which means the video summary did not contain the connected video segments, c) summarized video does not contain redundancy. The summary of the video having free repetition, but it is very complex to achieve.